EEE 361 Linear Algebra in Data Analysis and Machine Learning
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Linear algebra with applications to data science and computations. Applications of singular value decomposition, weighted least squares approximations, signal and image processing, principal component analysis, covariance and correlation matrices, directed and undirected graphs, matrix factorizations, neural nets and machine learning.
Credit units: 3 ECTS Credit units: 5, Prerequisite:
(CS 101 or CS 114 or CS 115) and (MATH 225 or MATH 220 or MATH 224 or MATH 241) and (MATH 230 or MATH 255 or MATH 250).
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